From b5ea5f3b0ef01b651806cb368cc7a7e51437a77c Mon Sep 17 00:00:00 2001 From: ancri Date: Thu, 20 Jul 2023 23:20:04 -0400 Subject: [PATCH] consolidate Embedding.create calls into one (#543) --- .../vector_databases/pinecone/Gen_QA.ipynb | 18 +++++++----------- 1 file changed, 7 insertions(+), 11 deletions(-) diff --git a/examples/vector_databases/pinecone/Gen_QA.ipynb b/examples/vector_databases/pinecone/Gen_QA.ipynb index 076d6bf..2aa5606 100644 --- a/examples/vector_databases/pinecone/Gen_QA.ipynb +++ b/examples/vector_databases/pinecone/Gen_QA.ipynb @@ -673,17 +673,13 @@ " # get texts to encode\n", " texts = [x['text'] for x in meta_batch]\n", " # create embeddings (try-except added to avoid RateLimitError)\n", - " try:\n", - " res = openai.Embedding.create(input=texts, engine=embed_model)\n", - " except:\n", - " done = False\n", - " while not done:\n", - " sleep(5)\n", - " try:\n", - " res = openai.Embedding.create(input=texts, engine=embed_model)\n", - " done = True\n", - " except:\n", - " pass\n", + " done = False\n", + " while not done:\n", + " try:\n", + " res = openai.Embedding.create(input=texts, engine=embed_model)\n", + " done = True\n", + " except:\n", + " sleep(5)\n", " embeds = [record['embedding'] for record in res['data']]\n", " # cleanup metadata\n", " meta_batch = [{\n",